Noise as an environmental factor in industry.

Towards prevention

Vitiligo is the most common depigmenting disorder which is determined by both genetic and environmental factors (1). During the last two decades, however, investigators have focused mainly on the genetics aspects of vitiligo rather than on the environmental side. For example, scholars have not only found more than 10 candidate genes for vitiligo (2-11), but also located several susceptibility genes to vitiligo on chromosomes one, four and six (8, 12-15). At the same time, the evidence base for environmental factors is weak despite the often heard expression that: ‘vitiligo, as a complex disease, is affected by both genetic and environmental factors’. In our current post-genomic era, genetics and genomics research is perceived to be ‘hot’ and epidemiological research to environmental risk factors runs the risk to be undervalued. Especially in the context of complex diseases, it is our duty to investigate all aspects of causation and not only the ‘sexy’ ones. Patients with vitiligo often assume that their disease is triggered by an environmental exposure such as sunlight, hair dye or paint (16). From anecdotal evidence (JBL) in clinical practice, we learned that trauma often seems to precede vitiligo as well. In many cases, the initial site of vitiligo is a wounded area. Gauthier recently proposed the melanocytorrhagy hypothesis which may explain this trauma-induced vitiligo (17, 18). Based on morphologic findings, his theory assumed melanocytorrhagy as the primary defect underlying melanocyte loss and integrated most of the possible triggering/precipitating/enhancing effects of other known factors, such as genetic, autoimmune, neural defections and impaired redox status (19-22). Despite the well-known nature-nurture debate on the causation of many complex diseases, no paper as yet systemically studied or reviewed environmental risk factors of vitiligo. This is disappointing. Some potential environmental factors were collected in our recently conducted genetic epidemiological study on vitiligo using 3742 patients (1, 23). Here, for discussion, we put forward an interesting but yet unpublished finding from this study on the relation between sunlight and vitiligo. We observed that exposure to sunlight might be negatively associated with vitiligo (OR 0.709, 95% CI: 0.453–1.111), especially for women (OR 0.506, 95% CI: 0.263–0.974). This finding is opposite to the experience described above. Today, however, no evidence is available that can prove or disprove the potential protective effect of sunlight on the incidence of vitiligo. It is well known that narrow-band UV-B can be used to treat vitiligo directly (24) and sunlight does accelerate repigmenting during the treatment by PUVA. Could sunlight, perhaps, even exert beneficial effects in vitiligo? As the heritability of vitiligo is observed to be around 50% (1), environment should contribute largely to the development of vitiligo. As with many complex diseases, we believe that an interleaving net constructed by both genetic and environmental factors should be considered as a general model of vitiligo pathogenesis. Identifying those disease-modulatory environmental factors is both a formidable and important task for epidemiologists and dermatologists in the next decade. We hope that this contribution will stimulate more research into the environmental determinants of vitiligo. As the genetic constitution of an individual cannot be changed, perhaps 1 day in-depth knowledge on environmental risk factors can prevent vitiligo in some individuals by changing the unfavourable environment.

Genetics of congenital heart defects: is it not all in the DNA?

Occupational health professionals such as occupational physicians (OPs) increasingly understand that in addition to health improvement, environmental factors (such as work adaptations) and personal factors (such as an employee's attitude towards return-to-work (RTW)) may stimulate employees on sick leave to return to work early. To target their professional interventions more specifically according to these factors, occupational health professionals need further insight into environmental and personal factors that stimulate RTW. The objectives of this study are (1) to identify which and how environmental and personal factors support RTW, and (2) to examine whether the International Classification of Functioning, Disability and Health (ICF) can be used to describe these factors. We performed interviews with 14 employees, 15 employers and 4 OPs from multiple organisations with varying organisational sizes and types of industry such as healthcare and education. We used a qualitative data analysis partially based on the Qualitative Analysis Guide of Leuven. The following environmental factors were found to support early RTW: 'social support from relatives', 'belief that work stimulates health', 'adequate cooperation between stakeholders in RTW' (e.g., employees, employers and OPs) and 'the employers' communicative skills'. One personal factor stimulated RTW: 'positive perception of the working situation' (e.g. enjoyment of work). Most factors stimulated RTW directly. In addition, adequate treatment and social support stimulated medical recovery. Environmental factors can either fully (social support, belief that RTW stimulates health), partially (effective cooperation), or not (employers' communicative skills) be described using ICF codes. The personal factor could not be classified because the ICF does not contain codes for personal factors. RTW interventions should aim at the environmental and personal factors mentioned above. Professionals can use the ICF to describe most environmental factors.

BackgroundBoth genetic and environmental factors contribute to human diseases. Most common diseases are influenced by a large number of genetic and environmental factors, most of which individually have only a modest effect on the disease. Though genetic contributions are relatively well characterized for some monogenetic diseases, there has been no effort at curating the extensive list of environmental etiological factors.ResultsFrom a comprehensive search of the MeSH annotation of MEDLINE articles, we identified 3,342 environmental etiological factors associated with 3,159 diseases. We also identified 1,100 genes associated with 1,034 complex diseases from the NIH Genetic Association Database (GAD), a database of genetic association studies. 863 diseases have both genetic and environmental etiological factors available. Integrating genetic and environmental factors results in the "etiome", which we define as the comprehensive compendium of disease etiology. Clustering of environmental factors may alert clinicians of the risks of added exposures, or synergy in interventions to alter these factors. Clustering of both genetic and environmental etiological factors puts genes in the context of environment in a quantitative manner.ConclusionIn this paper, we obtained a comprehensive list of associations between disease and environmental factors using MeSH annotation of MEDLINE articles. It serves as a summary of current knowledge between etiological factors and diseases. By combining the environmental etiological factors and genetic factors from GAD, we computed the "etiome" profile for 863 diseases. Comparing diseases across these profiles may have utility for clinical medicine, basic science research, and population-based science.

What drives the allergic march?

Tracing the Origins of Autism: A Spectrum of New Studies

ABSTRACTBackgroundCongenital solitary functioning kidney (CSFK) is an anomaly predisposing to hypertension, albuminuria and chronic kidney disease. Its aetiology is complex and includes genetic and environmental factors. The role of gene–environment interactions (G×E), although relevant for other congenital anomalies, has not yet been investigated. Therefore, we performed a genome-wide G×E analysis with six preselected environmental factors to explore the role of these interactions in the aetiology of CSFK.MethodsIn the AGORA (Aetiologic research into Genetic and Occupational/environmental Risk factors for Anomalies in children) data- and biobank, genome-wide single-nucleotide variant (SNV) data and questionnaire data on prenatal exposure to environmental risk factors were available for 381 CSFK patients and 598 healthy controls. Using a two-step strategy, we first selected independent significant SNVs associated with one of the six environmental risk factors. These SNVs were subsequently tested in G×E analyses using logistic regression models, with Bonferroni-corrected P-value thresholds based on the number of SNVs selected in step one.ResultsIn step one, 7–40 SNVs were selected per environmental factor, of which only rs3098698 reached statistical significance (P = .0016, Bonferroni-corrected threshold 0.0045) for interaction in step two. The interaction between maternal overweight and this SNV, which results in lower expression of the Arylsulfatase B (ARSB) gene, could be explained by lower insulin receptor activity in children heterozygous for rs3098698. Eight other G×E interactions had a P-value <.05, of which two were biologically plausible and warrant further study.ConclusionsInteractions between genetic and environmental factors may contribute to the aetiology of CSFK. To better determine their role, large studies combining data on genetic and environmental risk factors are warranted.

Transition Time to Full Nipple Feeding for Premature Infants With a History of Lung Disease

To compare the contributions of environmental and spatial factors in structuring assemblages of temperate stream fish on different spatial scales, I evaluated the distance decay of fish assemblage similarity and correlations among species compositions, environmental factors and geographical locations at medium (inter‐reach scale, spatial extent 40 km) and fine (inter‐microhabitat scale, spatial extent &lt;200 m) scales. Partial redundancy analysis and variation partitioning indicated that the ordinal rank of the relative importance of environmental and spatial factors differed among scales. At the medium scale, the distance decay of similarity of species composition was steep at approximately &gt;10‐km scale, and the assemblage structure was simply explained by the distance between sites and several environmental factors (e.g., elevation and current velocity). In contrast, the distance between microhabitats explained only a small portion of the variance in species composition at the fine scale, and fish assemblages were affected by several spatial patterns of habitat (or some environmental features associated with those spatial patterns). Environmental factors at the fine scale (e.g., substratum characteristics and presence/absence of cover) correlated with each other and were spatially structured, and their contribution to species variance was smaller than that at the medium scale. These results provide evidence for scale‐dependent alternation of the rank of the relative importance of environmental and spatial factors in structuring assemblages of stream fishes via the turnover of crucially contributing factors from medium to fine spatial scales.

The etiology of inflammatory bowel diseases (IBD) is multifactorial and is believed to result from an interplay of inappropriate immune response, gut microbiota, genetic susceptibility, and environmental factors.1 In the current issue of the Journal, Amnon Sonnenberg used epidemiological tools to explore potential clues pertaining to the etiology of IBD. The author analyzed the death rates in four diseases—Hodgkin lymphoma (HL), multiple sclerosis (MS), Crohn's disease (CD), and ulcerative colitis (UC)—in 21 countries from 1951 to 2020, using World Health Organization vital records. In general, the death rates from these four diseases tended to be high in most European countries and low for most non-European countries, and their associated death-rates were correlated and characterized by similar geographic distributions, which were all statistically significant. The author concluded that the remarkable similarity in geographic distribution implies the potential impact of shared environmental factors on the occurrence of these four diseases. Since typically, environmental risk factors have a universal effect, impacting all demographic segments of the population similarly, the author executed a second analysis for the age-specific death rates of the individual countries, correlated with each other. This analysis revealed that In HL and UC, the inter-age correlations started at age 5 years or less. In MS and CD, the inter-age correlations only started at age 15 years. These correlations suggest that the four diseases may share one or more common environmental risk factors. Such a conclusion could have far-reaching implications for how we understand disease etiology, potentially guiding future research into prevention and treatment strategies. The link between MS and inflammatory bowel diseases is well recognized.2 MS was associated with a 55% increased risk of IBD, and reciprocally, IBD patients had a 53% increased risk of MS.2 Genetic overlap was also described between these diseases.3 The linkage between IBD and HL is less established, although inflammatory mechanisms are part of HL pathogenesis.4, 5 EBV plays a major role in HL pathogenesis and perhaps also in MS, but is not a known predisposing factor in IBD. However, despite this innovative methodology and mind-provoking findings, some limitations need to be acknowledged. The study spans a compelling temporal range of 70 years, but this also opens the possibility of various biases and confounders, such as changes in diagnostic criteria, improvements in healthcare access, and differing reporting practices over time, which could all influence reported death rates. All four diseases were found correlated, and the lack of a negative control in the form of a disease tested by the same methodology and found uncorrelated with the other four stands out as yet another limitation. Finally, reliance on death rates is a well-documented surrogate marker of disease prevalence, but the advent of advanced medical treatments over the period covered by the study has likely reduced mortality rates, possibly differently between territories. The study does support previous knowledge demonstrating the influence of environmental factors on inflammatory bowel diseases. Past research has indicated that distinct environmental factors manifest differently in their impact on inflammatory bowel diseases in Western versus Eastern regions of the world.6 The under-representation of Asian and African populations in the present databases may limit the generalizability of findings. Indeed, EBV has been shown to affect Asian populations at an earlier age with over 90% sero-prevalence at age 5, as compared with Western populations in whom this rate is reached by age 227, thereby arguing against EBV as an environmental risk factor explaining the higher IBD rates in the West. In conclusion, this study represents a significant step forward in the epidemiological study of HL, MS, CD, and UC, and paves a conceptual path for further research. Nuanced outcome metrics, broader geographic representation, and a deep investigation into the shared environmental risk factors of IBD vis-à-vis other diseases may reveal unsuspected environmental factors responsible for the surge in IBD incidence in recent decades. This Editorial received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. The authors have no conflicts of interest to declare. The data underlying this article will be shared on reasonable request to the corresponding author.

Essential hypertension (EH) has become a major chronic disease around the world. To build a risk-predicting model for EH can help to interpose people's lifestyle and dietary habit to decrease the risk of getting EH. In this study, we constructed a EH risk-predicting model considering both environmental and genetic factors with support vector machine (SVM). The data were collected through Epidemiological investigation questionnaire from Beijing Chinese Han population. After data cleaning, we finally selected 9 environmental factors and 12 genetic factors to construct the predicting model based on 1200 samples, including 559 essential hypertension patients and 641 controls. Using radial basis kernel function, predictive accuracy via SVM with function with only environmental factor and only genetic factor were 72.8 and 54.4%, respectively; after considering both environmental and genetic factor the accuracy improved to 76.3%. Using the model via SVM with Laplacian function, the accuracy with only environmental factor and only genetic factor were 76.9 and 57.7%, respectively; after combining environmental and genetic factor, the accuracy improved to 80.1%. The predictive accuracy of SVM model constructed based on Laplacian function was higher than radial basis kernel function, as well as sensitivity and specificity, which were 63.3 and 86.7%, respectively. In conclusion, the model based on SVM with Laplacian kernel function had better performance in predicting risk of hypertension. And SVM model considering both environmental and genetic factors had better performance than the model with environmental or genetic factors only.

Update on epigenetics in allergic disease

ADHD: The Mammoth Task of Disentangling Genetic, Environmental, and Developmental Risk Factors.

BackgroundThe relative contributions of genetic and environmental factors versus unavoidable stochastic risk factors to the variation in cancer risk among tissues have become a widely-discussed topic. Some claim that the stochastic effects of DNA replication are mainly responsible, others believe that cancer risk is heavily affected by environmental and hereditary factors. Some of these studies made evidence from the correlation analysis between the lifetime number of stem cell divisions within each tissue and tissue-specific lifetime cancer risk. However, they did not consider the measurement error in the estimated number of stem cell divisions, which is caused by the exposure to different levels of genetic and environmental factors. This will obscure the authentic contribution of environmental or inherited factors.MethodsIn this study, we proposed two distinct modeling strategies, which integrate the measurement error model with the prevailing model of carcinogenesis to quantitatively evaluate the contribution of hereditary and environmental factors to cancer development. Then, we applied the proposed strategies to cancer data from 423 registries in 68 different countries (global-wide), 125 registries across China (national-wide of China), and 139 counties in Shandong province (Shandong provincial, China), respectively.ResultsThe results suggest that the contribution of genetic and environmental factors is at least 92% to the variation in cancer risk among 17 tissues. Moreover, mutations occurring in progenitor cells and differentiated cells are less likely to be accumulated enough for cancer to occur, and the carcinogenesis is more likely to originate from stem cells. Except for medulloblastoma, the contribution of genetic and environmental factors to the risk of other 16 organ-specific cancers are all more than 60%.ConclusionsThis work provides additional evidence that genetic and environmental factors play leading roles in cancer development. Therefore, the identification of modifiable environmental and hereditary risk factors for each cancer is highly recommended, and primary prevention in early life-course should be the major focus of cancer prevention.